Use of artificial intelligence for prediction of work accidents with biological risks in healthcare professionals

Detalhes bibliográficos
Autor(a) principal: Groto, Anderson Dillmann
Data de Publicação: 2021
Outros Autores: Perlin, Cássio Marques, Andrade, Sonia Mara de, Salamanca, Mayara Angélica Bolson
Tipo de documento: Artigo
Idioma: por
Título da fonte: Research, Society and Development
Texto Completo: https://rsdjournal.org/index.php/rsd/article/view/19743
Resumo: This study developed a software that calculates the chance of the health professional having zero, one, two, three or four or more accidents with biological hazards. Data from 111 questionnaires of health workers in primary and emergency care were used. The program achieved 95% accuracy in the training set (n=88) and 74% in the test set (n=23). The statistically significant associations, which also relied on data from 1,094 work accident reports, were greater abandonment of follow-up by physicians after an accident with biological materials in comparison with other professionals (p=0.02), nursing technicians and a higher prevalence of accidents with biological materials than other professionals (p<0.001), emergency care workers have more accidents with biological materials than primary care professionals (p<0.001) and increased follow-up abandonment after an accident with biological materials in the 2016-2018 period compared to 2007-2009 (p<0.001).
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spelling Use of artificial intelligence for prediction of work accidents with biological risks in healthcare professionalsUso de la inteligencia artificial para la predicción de accidentes de trabajo con materiales biológicos en profesionales de la saludUso da inteligência artificial para predição de acidentes de trabalho com materiais biológicos em profissionais da saúdeInteligência ArtificialAcidentes OcupacionaisSaúde do TrabalhadorAtenção primária à saúde.Inteligencia ArtificialAccidentes LaboralesSalud LaboralAtención primaria.Artificial IntelligenceOccupational AccidentsOccupational HealthPrimary health care.This study developed a software that calculates the chance of the health professional having zero, one, two, three or four or more accidents with biological hazards. Data from 111 questionnaires of health workers in primary and emergency care were used. The program achieved 95% accuracy in the training set (n=88) and 74% in the test set (n=23). The statistically significant associations, which also relied on data from 1,094 work accident reports, were greater abandonment of follow-up by physicians after an accident with biological materials in comparison with other professionals (p=0.02), nursing technicians and a higher prevalence of accidents with biological materials than other professionals (p<0.001), emergency care workers have more accidents with biological materials than primary care professionals (p<0.001) and increased follow-up abandonment after an accident with biological materials in the 2016-2018 period compared to 2007-2009 (p<0.001).El objetivo de este estudio es desarrollar un programa informático que calcule la probabilidad de que un profesional de salud tenga cero, uno, dos, tres o cuatro o más accidentes con riesgo biológico. Se utilizaron datos de 111 cuestionarios de trabajadores de la atención primaria y de urgencias. El programa alcanzó 95% de precisión en el conjunto entrenamiento (n=88) y 74% en el conjunto de prueba (n=23). Las asociaciones estadísticamente significativas, que también incluyeron datos de 1.094 Comunicaciones de Accidentes de Trabajo, fueron el mayor abandono del seguimiento por parte de los médicos tras un accidente con materiales biológicos en comparación con otros profesionales (p=0,02), los técnicos de enfermería y mayor prevalencia de accidentes con materiales biológicos que otros profesionales (p<0,001), los trabajadores de urgencias presentan más accidentes con material biológico que los profesionales de atención primaria (p<0,001) y aumento del abandono tras accidente con material biológico en el trienio 2016-2018 respecto a 2007-2009 (p<0,001).Este estudo buscou desenvolver um software que calcula a chance de o profissional de saúde ter zero, um, dois, três ou quatro ou mais acidentes com riscos biológicos. Para tal foram utilizados dados de 111 questionários de trabalhadores da saúde da atenção primária e pronto atendimento. O programa atingiu 95% de acurácia no conjunto de treinamento (n=88) e 74% no conjunto de teste (n=23). As associações estatisticamente significantes, que contaram também com dados de 1.094 Comunicações de Acidente de Trabalho, foram maior abandono do acompanhamento por médicos após acidente com materiais biológicos na comparação com outros profissionais (p=0.02), técnicos em enfermagem e maior prevalência de acidentes com materiais biológicos que outros profissionais (p<0.001), trabalhadores de pronto atendimento apresentam mais acidentes com materiais biológicos que profissionais da atenção primária (p<0.001) e aumento do abandono após acidente com materiais biológicos no triênio 2016-2018 na comparação com 2007-2009 (p<0.001).Research, Society and Development2021-09-14info:eu-repo/semantics/articleinfo:eu-repo/semantics/publishedVersionapplication/pdfhttps://rsdjournal.org/index.php/rsd/article/view/1974310.33448/rsd-v10i12.19743Research, Society and Development; Vol. 10 No. 12; e93101219743Research, Society and Development; Vol. 10 Núm. 12; e93101219743Research, Society and Development; v. 10 n. 12; e931012197432525-3409reponame:Research, Society and Developmentinstname:Universidade Federal de Itajubá (UNIFEI)instacron:UNIFEIporhttps://rsdjournal.org/index.php/rsd/article/view/19743/18007Copyright (c) 2021 Anderson Dillmann Groto; Cássio Marques Perlin; Sonia Mara de Andrade; Mayara Angélica Bolson Salamancahttps://creativecommons.org/licenses/by/4.0info:eu-repo/semantics/openAccessGroto, Anderson DillmannPerlin, Cássio Marques Andrade, Sonia Mara de Salamanca, Mayara Angélica Bolson 2021-11-14T20:26:51Zoai:ojs.pkp.sfu.ca:article/19743Revistahttps://rsdjournal.org/index.php/rsd/indexPUBhttps://rsdjournal.org/index.php/rsd/oairsd.articles@gmail.com2525-34092525-3409opendoar:2024-01-17T09:39:35.144135Research, Society and Development - Universidade Federal de Itajubá (UNIFEI)false
dc.title.none.fl_str_mv Use of artificial intelligence for prediction of work accidents with biological risks in healthcare professionals
Uso de la inteligencia artificial para la predicción de accidentes de trabajo con materiales biológicos en profesionales de la salud
Uso da inteligência artificial para predição de acidentes de trabalho com materiais biológicos em profissionais da saúde
title Use of artificial intelligence for prediction of work accidents with biological risks in healthcare professionals
spellingShingle Use of artificial intelligence for prediction of work accidents with biological risks in healthcare professionals
Groto, Anderson Dillmann
Inteligência Artificial
Acidentes Ocupacionais
Saúde do Trabalhador
Atenção primária à saúde.
Inteligencia Artificial
Accidentes Laborales
Salud Laboral
Atención primaria.
Artificial Intelligence
Occupational Accidents
Occupational Health
Primary health care.
title_short Use of artificial intelligence for prediction of work accidents with biological risks in healthcare professionals
title_full Use of artificial intelligence for prediction of work accidents with biological risks in healthcare professionals
title_fullStr Use of artificial intelligence for prediction of work accidents with biological risks in healthcare professionals
title_full_unstemmed Use of artificial intelligence for prediction of work accidents with biological risks in healthcare professionals
title_sort Use of artificial intelligence for prediction of work accidents with biological risks in healthcare professionals
author Groto, Anderson Dillmann
author_facet Groto, Anderson Dillmann
Perlin, Cássio Marques
Andrade, Sonia Mara de
Salamanca, Mayara Angélica Bolson
author_role author
author2 Perlin, Cássio Marques
Andrade, Sonia Mara de
Salamanca, Mayara Angélica Bolson
author2_role author
author
author
dc.contributor.author.fl_str_mv Groto, Anderson Dillmann
Perlin, Cássio Marques
Andrade, Sonia Mara de
Salamanca, Mayara Angélica Bolson
dc.subject.por.fl_str_mv Inteligência Artificial
Acidentes Ocupacionais
Saúde do Trabalhador
Atenção primária à saúde.
Inteligencia Artificial
Accidentes Laborales
Salud Laboral
Atención primaria.
Artificial Intelligence
Occupational Accidents
Occupational Health
Primary health care.
topic Inteligência Artificial
Acidentes Ocupacionais
Saúde do Trabalhador
Atenção primária à saúde.
Inteligencia Artificial
Accidentes Laborales
Salud Laboral
Atención primaria.
Artificial Intelligence
Occupational Accidents
Occupational Health
Primary health care.
description This study developed a software that calculates the chance of the health professional having zero, one, two, three or four or more accidents with biological hazards. Data from 111 questionnaires of health workers in primary and emergency care were used. The program achieved 95% accuracy in the training set (n=88) and 74% in the test set (n=23). The statistically significant associations, which also relied on data from 1,094 work accident reports, were greater abandonment of follow-up by physicians after an accident with biological materials in comparison with other professionals (p=0.02), nursing technicians and a higher prevalence of accidents with biological materials than other professionals (p<0.001), emergency care workers have more accidents with biological materials than primary care professionals (p<0.001) and increased follow-up abandonment after an accident with biological materials in the 2016-2018 period compared to 2007-2009 (p<0.001).
publishDate 2021
dc.date.none.fl_str_mv 2021-09-14
dc.type.driver.fl_str_mv info:eu-repo/semantics/article
info:eu-repo/semantics/publishedVersion
format article
status_str publishedVersion
dc.identifier.uri.fl_str_mv https://rsdjournal.org/index.php/rsd/article/view/19743
10.33448/rsd-v10i12.19743
url https://rsdjournal.org/index.php/rsd/article/view/19743
identifier_str_mv 10.33448/rsd-v10i12.19743
dc.language.iso.fl_str_mv por
language por
dc.relation.none.fl_str_mv https://rsdjournal.org/index.php/rsd/article/view/19743/18007
dc.rights.driver.fl_str_mv https://creativecommons.org/licenses/by/4.0
info:eu-repo/semantics/openAccess
rights_invalid_str_mv https://creativecommons.org/licenses/by/4.0
eu_rights_str_mv openAccess
dc.format.none.fl_str_mv application/pdf
dc.publisher.none.fl_str_mv Research, Society and Development
publisher.none.fl_str_mv Research, Society and Development
dc.source.none.fl_str_mv Research, Society and Development; Vol. 10 No. 12; e93101219743
Research, Society and Development; Vol. 10 Núm. 12; e93101219743
Research, Society and Development; v. 10 n. 12; e93101219743
2525-3409
reponame:Research, Society and Development
instname:Universidade Federal de Itajubá (UNIFEI)
instacron:UNIFEI
instname_str Universidade Federal de Itajubá (UNIFEI)
instacron_str UNIFEI
institution UNIFEI
reponame_str Research, Society and Development
collection Research, Society and Development
repository.name.fl_str_mv Research, Society and Development - Universidade Federal de Itajubá (UNIFEI)
repository.mail.fl_str_mv rsd.articles@gmail.com
_version_ 1797052808284864512

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